The Bubble Box plot allows you to visualize binding data for a set of samples and compare basic statistical parameters such as mean, median and group data for aggregate statistics. It presents the data for each glycan vs each sample in the form of bubbles or points which can be dispersed or aggregated.
Creating a Bubble Box Plot
In order to produce a Bubble Box plot, load data into selections, check the settings for the colors of the box plots and click on the Bubble Box plot button. This will produce the Bubble Box plot.
Navigating a Bubble Box Plot
- Putting your mouse over individual “bubbles” (points) hides all other points for all samples, highlighting the data for only specific glycan for all samples. This allows for quick comparison of the data for a single glycan.
Clicking on a bubble freezes the view to take a snapshot, if the user would like to save such image. - Ctrl+click on a bubble to add the structure to the Selected
Structures popup. - Clicking on the “Jitter Data Points Toggle”
jitters the data points to reduce overlap for a better visualization of many data points.
- Clicking on the “Spray Data Points Toggle”
sprays the data points allowing for separation of the higher binders better as compared to the lower binders. An alternative way to visualize and highlight data.
- “Draw Box Plot Toggle”
switch shows or hides the box plot.
- “Draw Mean Line Toggle”
switch shows or hides the mean line along with the standard deviation.
- “ANOVA”
performs a one-way ANOVA. It produces the F-value and the p-value below the plot. If the p-value is below the threshold (as set in the settings), a post-hoc Tukey-Honestly Significantly Different (HSD) analysis is performed between the samples, and the p-value for the differences between the samples is shown below the plot if the p-value is below the threshold. - “Group Samples”
button takes you through a step by step wizard as discussed below to group your samples into groups to get aggregate data by combining data for samples. This can be useful to aggregate similar samples with each other to view aggregate data. For example male samples vs female samples.
Group Samples
Group Samples allows you to aggregate the data into groups which can then be analyzed for their statistical parameters. To group the samples
- Click on the button to begin grouping.
Choose the number of groups you would like to create and click the 
next button. To start over the process you can click this button and it will start you over the grouping process.
Type in the Group Labels and choose the Group Colors. Note- these cannot be changed later on so choose them appropriately.
- Choose the samples you would like to put in the groups by selecting the samples which appear in the list.
To make it easier to add samples to the group, you can filter the list by typing parts of names by which you would group your samples. Then click on the
select all button, to select the samples which were filtered.
Click the
Add button to add the samples to the group. - Step 4 will be repeated for all the groups.
After all groups are allocated, a final option will appear and you can group your samples by clicking on the 
Group button. The software will redraw a bubble box plot with the grouped data.
After this, clicking on the group button again, an options to Ungroup the data or to Filter Grouped Data will also appear which will allow you to filter your Grouped Bubble Box Plot by glycan Name. Note there is no undo after this step and therefore we recommend you save your session before performing this.
Settings
Choose Box and Line Color OR Use Sample Colors: Allows you to customize the colors of the box plot and the mean lines.- Custom Size: Select the check box and adjust the width and height to customize the scale of your Bubble Box Plots.
- Choose p-value cutoff: set the p-value confidence levels for the ANOVA analysis
- Custom Y-Axis: Check this box and set the lower and upper limit values to customize the Y-axis.
- Update Plot: update plot button allows you to update the bubble box plot keeping your groups intact. Thus you can use this function to update the plot with custom size and Y-axis to get an updated plot.